Using data from an MVP
This article is part of “Intro to Data-Driven Product Management,” a series of posts from the crew at Notion to help new (and experienced) Product Managers use data to create better products.
Lean Startup founder Eric Ries describes a Minimum Viable Product (MVP) as “that version of a new product which allows a team to collect the maximum amount of validated learning about customers with the least effort.” In the Lean methodology, you can ensure you are building the right product by testing your assumptions as quickly as possible. MVP can be used for both new products and for features in an existing product.
Whether you‘re learning if the product idea is relevant or if the UI you’ve created works for users, the goal of building an MVP is to understand if your solution adds value to the customer. In order to do this, you can test whether your solution resonates with potential users.
Depending on what you’re testing, the MVP can be as simple as an InVision prototype or even a piece of paper, and as complex as a fully developed web application. The objective isn’t to make something cheap or simple, it’s to make something that takes the minimum effort to prove or disprove your hypothesis. Your early adopters (AKA “earlyvangelists”) will be users who understand the value you’re offering even if there are initially gaps.
The MVP can be as simple as an InVision prototype or even a piece of paper, and as complex as a fully developed web application.
When collecting data about your MVP, get only the feedback you need to discover you’re on the right track. Once you have a clear signal, you can move on to developing your idea more fully and testing new things. Along with prototyping tools like InVision, you can get data with UI/UX testing like UserTesting.com or from beta testing a product or feature in a beta group.
Along with “Minimum Viable Product,” the notions of “Minimum Valuable Product or “Minimum Loveable Product” can help you continue to iterate once you’ve found a general solution that works. In these cases, you’re trying to build the product that customers will actually pay for or refer others to use. In the example from “Lean Analytics” that we talked about in the last lesson, these concepts would be applied to products that have emerged from the “Stickiness” phase into the “Virality” and “Revenue” phases. In the Lean system, you are constantly iterating to discover how to better serve customers, and the data you collect from these tests can be very helpful to collect and review over time so you understand what to build next.
In addition to the MVP, there are other tests that can help you understand whether you’re going in the right direction. You can create landing pages that speak to the value you offer or intend to offer and test their conversion. You can create advertising against the product idea you have and measure performance. You can run A/B tests, where you change one aspect of your marketing page or sales email to see what most resonates. Product marketers often use these tactics to help Product Managers and Owners understand customer signal before developing new products or features.
Other user research can play an important part by providing qualitative data that can help you understand what to build. User interviews, market research and customer feedback are all great sources of data for your product. In all cases, the most important thing to track are the problems that need to be solved, rather than the solutions users may propose. As a product manager, your job is to discover and guide the right solution for users’ problems, not to collect solutions for specific use cases.
“Customers aren’t spending their spare time dreaming up ideas for your product. They ask for a feature because their project has a requirement, and so will propose a solution based on their use case at that time. To get past the specific, you need to get to the problem that the user is having. What are they trying to achieve by way of the solution they have proposed? By asking those questions you can find out the real need, and sometimes you can help them solve it right away, without having to add an extra feature.”
— Rachel Andrew, A List Apart
Notion is a tool to help team leaders collaborate and communicate around their metrics. We’ll discuss user research in more detail in a future lesson, so stay tuned!
